Creating a provincial post COVID‐19 interdisciplinary clinical care network as a learning health system during the pandemic: Integrating clinical care and research

Abstract Introduction Coronavirus Disease‐2019 (COVID‐19) affects multiple organ systems in the acute phase and also has long‐term sequelae. Research on the long‐term impacts of COVID‐19 is limited. The Post COVID‐19 Interdisciplinary Clinical Care Network (PC‐ICCN), conceived in July 2020, is a provincially funded resource that is modelled as a Learning Health System (LHS), focused on those people with persistent symptoms post COVID‐19 infection. Methods The PC‐ICCN emerged through collaboration among over 60 clinical specialists, researchers, patients, and health administrators. At the core of the network are the post COVID‐19 Recovery Clinics (PCRCs), which provide direct patient care that includes standardized testing and education at regular follow‐up intervals for a minimum of 12 months post enrolment. The PC‐ICCN patient registry captures data on all COVID‐19 patients with confirmed infection, by laboratory testing or epi‐linkage, who have been referred to one of five post COVID‐19 Recovery Clinics at the time of referral, with data stored in a fully encrypted Oracle‐based provincial database. The PC‐ICCN has centralized administrative and operational oversight, multi‐stakeholder governance, purpose built data collection supported through clinical operations geographically dispersed across the province, and research operations including data analytics. Results To date, 5364 patients have been referred, with an increasing number and capacity of these clinics, and 2354 people have had at least one clinic visit. Since inception, the PC‐ICCN has received over 30 research proposal requests. This is aligned with the goal of creating infrastructure to support a wide variety of research to improve care and outcomes for patients experiencing long‐term symptoms following COVID‐19 infection. Conclusions The PC‐ICCN is a first‐in‐kind initiative in British Columbia to enhance knowledge and understanding of the sequelae of COVID‐19 infection over time. This provincial initiative serves as a model for other national and international endeavors to enable care as research and research as care.

time of referral, with data stored in a fully encrypted Oracle-based provincial database. The PC-ICCN has centralized administrative and operational oversight, multistakeholder governance, purpose built data collection supported through clinical operations geographically dispersed across the province, and research operations including data analytics.
Results: To date, 5364 patients have been referred, with an increasing number and capacity of these clinics, and 2354 people have had at least one clinic visit. Since inception, the PC-ICCN has received over 30 research proposal requests. This is aligned with the goal of creating infrastructure to support a wide variety of research to improve care and outcomes for patients experiencing long-term symptoms following COVID-19 infection. infection on people and the health care system is unknown. [1][2][3] International estimates indicate that 10% to 20% of individuals recovering from COVID-19 experience long-term complications. 4 Given the multiplicity of organ systems affected and the susceptibility of individuals with substantial comorbidity to the infection, impacts are likely significant. [5][6][7] As the focus of the pandemic shifts from acute management of disease, ensuring emphasis on treatment and support for patients with long-term complications is needed.
The novelty and complexity of COVID-19 combined with the evolving evidence around long-term outcomes indicates the need to rapidly translate new knowledge that will inform the public, guide clinical practice, and drive health policy. To generate sufficient data to evaluate and advance patient care and health policy for COVID-19, data from many patients across various geographic settings are needed. The variability in clinical presentation combined with small numbers of patients in any practice or jurisdiction necessitates broader collaborations as forums for learning. Learning Health Systems (LHS) provide a framework for organizing people and resources to address common challenges and support the rapid dissemination of findings to enable decision-making. [8][9][10] Distinguishing characteristics of a LHS include recognizing the need to learn from routine patient care and the enablement to do so through fostering a culture of inquiry, facilitating partnerships between research and clinical practice, and purpose-built robust data infrastructure. 8,[10][11][12][13] British Columbia (BC), Canada's westernmost province, announced its first COVID-19 case in January 2020 and progressed to a formal public health emergency 2 months later as community transmission increased. 14,15 BC's landmass spans approximately 950 000 km 2 with an estimated population of 5 million people. At the pandemic's start, BC experienced variable incidences of the virus and uneven access to healthcare services across the geographically diverse province, including access to testing, acute care, and dedicated outpatient follow-up.
The post COVID-19 Interdisciplinary Clinical Care Network (PC-ICCN) was conceived in May 2020 in recognition of an emerging need for specialized coordinated care for a subset of post COVID-19 patients with persistent symptoms (now recognized as long-haul COVID, long COVID, or Post Acute Sequelae of COVID-19, PASC). 16 Modelled as a LHS, the PC-ICCN evolved iteratively to address patient care goals, facilitate clinical collaboration, and enhance research integration. 17,18 Herein, we describe the PC-ICCN and data infrastructure developed to support ongoing clinical care and research.

| PC-ICCN OVERVIEW AND NETWORK OBJECTIVES
Based on the known physiology of the whole-body distribution of the angiotensin converting enzyme-2 receptor and the virus binding to the receptor, the possibility of multisystem involvement became apparent early in the pandemic 19 • Provincial steering committee comprising of clinicians, leaders from all health authorities, the Ministry of Health, patient partners, and researchers to increase the accountability of the PC-ICCN with bi-directional support from the committee to help address roadblocks experience. • Governance structures including a core steering group, a clinical care coordination working group, a research coordination working group, and a data information coordination working group.

Legal
Provides guidance and scope to the conduct of the LHS within regulatory and legal realm. This encompasses privacy legislation for safeguarding personal health information as well as regulatory guidance for professional practice and healthcare delivery.
• PROMIS is an administrative health care database that stores fully identified patient-level data and is managed by BC Provincial Renal Agency under regulation by the provincial government of BC.

Ethical
Promotes structures and processes aimed to guide ethical approach to continuous learning. Embedded learning in health systems may create a lack of clear distinction between clinical practice, quality improvement, evaluation, and research.
• All research applications must have a separate Research Ethics Board approval prior to PC-ICCN data release to a requesting researcher. The primary goals of the network were the following: (a) to demonstrate the ability to stand up interdisciplinary clinics offering care and education to patients suffering from long COVID, with standardized follow up and data capture in order to (b) acquire the expertise and experience to deliver high quality interdisciplinary care, (c) to develop accessible tools for primary care physicians and patients to enable capacity building with that acquired expertise, and (d) to use data acquired in this context to inform the evolution of care models.
The secondary goals were to normalize the embedding of research into clinical care, and to create a culture of collaboration across different clinical and research teams.

| THE PC-ICCN AS A LEARNING HEALTH SYSTEM
LHSs represent environments wherein culture both supports and facilitates continuous improvement in patient care and care processes through fostering community, providing infrastructure, and aligning clinical, quality, and academic incentives. Menear et al propose six pillars as the foundation of a LHS: scientific, social, technological, policy, legal and ethical. 10 The components of the PC-ICCN aligned with these pillars, presented and defined in Table 1, serve to enable communities to complete learning cycles around prioritized issues. 10 The PC-ICCN aligns with the LHS framework by leveraging data generated as part of clinical care to create evidence needed to address questions patients, clinicians, and policy-makers need answers to in selecting or providing patient care. The complete structure of the PC-ICCN Network is depicted in Figure 1.

| PC-ICCN patient registry
Patient registries embedded into care delivery support the standardization of data collection and enhance clinician collaboration resulting in improved patient care. [30][31][32] In addition, such registries advance the understanding of the natural history and progression of disease and thus, the ability to optimize care for current and future patients. 33  A core dataset inclusive of clinical, patient-reported, and laboratory data ( Table 2) is captured on all patients referred to the PCRC as detailed in Figure 3. Once a patient is registered in the registry, laboratory results are automatically uploaded through established and sanctioned interfaces. Patients are assessed using standardized testing protocols, including symptom questionnaires vetted or developed by a provincial working group of patients and interdisciplinary clinicians.
Where validated questionnaires for symptoms of fatigue, breathlessness, depression existed, these were used. The core dataset (Table 2) includes demographic, clinical, laboratory, and imaging data, with a balance between patient burden and comprehensiveness.

| PC-ICCN biobank
All patients referred to a PCRC are invited to participate in the provin-  This model has proven effective at improving the outcomes of chronic conditions in BC, for example demonstrating that patients with chronic kidney disease managed in interdisciplinary care clinics have better metabolic parameters and improved survival on dialysis compared to those managed solely by nephrologists. 47